Legal claims defining the scope of protection. Each claim is shown in both the original legal language and a plain English translation.
1. A method for controlling an amount of power at a substation of a power distribution system (PDS), comprising steps: providing an amount of renewable generation to the substation of PDS using buses that inject renewable energy into the PDS using a transmission system at the substation for sharing renewable energy consumption between a predetermined number of load devices based upon predetermined aggregated load control plans to each load device to the substation of the PDS for a scheduling period; identifying from the scheduling period if situations in which an aggregated demand at the substation exceeds a predetermined limit, and upon determination of the aggregated demand exceeding the predetermined limit, then determine for a next scheduling period aggregate load control plans to each load device to the substation of the PDS in which an aggregated demand at the substation does exceed the predetermined limit for the next scheduling period, wherein the aggregated demand for the next scheduling period is determined based on an energy demand of each load device and an amount of availability of renewable energy from the renewable generation; determining the aggregate load control plans for each load device to the substation of the PDS for the next scheduling period, based on specifying decoupled price components for the substation of the PDS for all pricing intervals of the next scheduling period; acquiring forecasts of load demands and renewable generations of the PDS for each forecasting intervals of the next scheduling period; determining load control plans for all aggregated loads with flexibility for each forecasting interval of the next scheduling period, wherein the load control plans are optimal; evaluating demand fluctuations at the substation based on the load control plans, and adjusting decoupled price components for the substation until the demand fluctuations at the substation are within a tolerance range; allocating the aggregated load control plans to each load device of the substation of the PDS so the aggregated demand at the substation does not exceed the predetermined limit for the next scheduling period; and controlling an amount of power at the substation of the PDS for the next scheduling period by controlling each load device of the substation of the PDS based on adjusting an amount of power consumption and an amount of operation time of the load device during the next scheduling period according to the aggregated load control plans by lowering reducible loads, dropping removable loads and scheduling transferrable loads, according to the aggregate load control plans for each load device of the substation of the PDS, wherein the steps are performed in a processor connected to a memory, an input interface and an output interface.
Power systems and substations. Managing power at a substation to prevent aggregated demand from exceeding a predetermined limit, especially with fluctuating renewable energy sources. The invention provides renewable generation to a substation using buses that inject this energy into a power distribution system. This renewable energy is shared among a set number of load devices based on aggregated load control plans for a specific scheduling period. The system identifies if the aggregated demand at the substation exceeds a limit during a scheduling period. If it does, it determines new aggregated load control plans for the next scheduling period. These new plans aim to ensure the aggregated demand does not exceed the limit, considering the energy demand of each load device and the availability of renewable energy. The plans are determined by specifying decoupled price components for all pricing intervals of the next scheduling period. Forecasts of load demands and renewable generations are acquired for the next scheduling period. Optimal load control plans are determined for aggregated loads with flexibility for each forecasting interval. Demand fluctuations at the substation are evaluated, and the decoupled price components are adjusted until these fluctuations are within a tolerance range. Finally, the aggregated load control plans are allocated to each load device so that the aggregated demand at the substation stays within the limit for the next scheduling period. Power at the substation is controlled by managing each load device's power consumption and operation time according to these plans, which involves lowering reducible loads, dropping removable loads, and scheduling transferable loads. These steps are executed by a processor connected to memory and
2. The method of claim 1 , wherein each scheduling period includes at least one pricing intervals, each pricing interval includes at least one load and generation forecasting interval, and the PDS includes a substation, at least one load with flexibility, at least one renewable generation and radially configured.
This invention relates to a method for managing power distribution systems (PDS) with renewable energy integration and flexible loads. The system addresses the challenge of balancing intermittent renewable generation with variable demand in a radial distribution network. The method involves dividing time into scheduling periods, each containing at least one pricing interval. Each pricing interval further includes at least one load and generation forecasting interval, allowing for dynamic adjustments based on real-time conditions. The PDS includes a substation, at least one flexible load, and at least one renewable energy source, all configured in a radial topology. The system optimizes energy distribution by leveraging forecasting intervals to predict and respond to fluctuations in supply and demand, ensuring grid stability and efficient resource utilization. The flexible loads can adjust their consumption based on pricing signals or operational constraints, while renewable generation is integrated to maximize clean energy usage. The radial configuration simplifies power flow management, reducing complexity in coordination between distributed resources. This approach enhances grid reliability, reduces energy costs, and supports higher penetration of renewable energy sources.
3. The method of claim 1 , wherein a set of decoupled price components is specified for the substation for each pricing interval of the next scheduling period, including: a base energy price component used to charge for an active power extracted from the substation by the PDS, an up reserve price component used to charge for an up reserve usage when the active power extracted from the substation is above an upper limit of a pre-determined normal range, where the up reserve usage is determined as a difference between active power extracted from the substation and the upper limit, a down reserve price component used to charge for a down reserve usage when the active power extracted from the substation is below a lower limit of the pre-determined normal range, where the down reserve usage is determined as a difference between the lower limit and the active power extracted from the substation, an up reserve variation price component used to charge for an up reserve usage variation between two consecutive pricing intervals, where the up reserve usage variation is determined as an absolute value of a difference between the up reserve usage at a current pricing interval and the up reserve usage at a previous pricing interval, and a down reserve variation price component used to charge for a down reserve usage variation between two consecutive pricing intervals, where the down reserve usage variation is determined as an absolute value of a difference between the down reserve usage at current pricing interval and the down reserve usage at previous pricing interval.
This invention relates to a method for pricing electricity distribution from a substation to a power distribution system (PDS) during a scheduling period. The method addresses the challenge of dynamically pricing electricity based on varying demand and reserve requirements, ensuring fair and efficient cost allocation. The method involves specifying a set of decoupled price components for the substation for each pricing interval within the next scheduling period. These components include a base energy price for active power extracted from the substation, an up reserve price for power usage exceeding an upper limit of a predefined normal range, and a down reserve price for power usage below a lower limit of the normal range. The up and down reserve usages are calculated as the differences between the actual power extracted and the respective limits. Additionally, the method includes up and down reserve variation price components to account for changes in reserve usage between consecutive pricing intervals. The up reserve variation price charges for the absolute difference in up reserve usage between the current and previous intervals, while the down reserve variation price charges for the absolute difference in down reserve usage between the same intervals. This approach ensures that pricing reflects both steady-state and dynamic variations in power demand and reserve requirements, promoting efficient energy distribution and cost transparency.
4. The method of claim 2 , wherein the load with flexibility is a reducible load with a demand reduced with an inconvenience cost, a removable load with a demand partially or completely removed with a penalty cost, a transferrable load with a demand deferred to a later time or advanced to an earlier time within the scheduling period, and the demand is increased when transferred to other interval, and wherein the load control plan specifies an amount of active power reduction for each reducible load, the amount of active power drop for each removable load, and a transferred intervals and an amount of transferred active powers for each transferrable load; and a load is connected to a bus with WYE-connection or DELTA-connection.
This invention relates to load management in electrical power systems, specifically addressing the challenge of balancing supply and demand by dynamically adjusting flexible loads. The system categorizes loads into three types: reducible loads, where demand is reduced with an associated inconvenience cost; removable loads, where demand is partially or fully removed with a penalty cost; and transferable loads, where demand is deferred or advanced within a scheduling period, with adjustments in active power when shifted to other intervals. The load control plan specifies the exact active power reduction for reducible loads, the active power drop for removable loads, and the timing and power adjustments for transferable loads. Additionally, the loads are connected to a bus using either WYE or DELTA configurations. This approach optimizes energy distribution by strategically managing load flexibility, minimizing costs, and maintaining system stability. The method ensures efficient power allocation while accounting for the operational constraints and economic impacts of load adjustments.
5. The method of claim 4 , wherein a DELTA-connected load between phases is be converted to equivalent WYE-connected loads at each phase according to a power factor, cos ϕ D according to: P D xy - x = β D + P D xy , P D xy - y = β D - P D xy , β D + = 1 2 + 3 6 tan ϕ D , β D - = 1 2 - 3 6 tan ϕ D , wherein P D xy is the active power of the DELTA-connected load between phase x and phase y, P D xy-x and P D xy-y are the active powers of equivalent loads at phase x and phase y, β D + and β D − are conversion factors.
This invention relates to electrical power systems, specifically methods for converting DELTA-connected loads into equivalent WYE-connected loads. DELTA connections are common in three-phase power systems, where loads are connected between phases rather than between a phase and a neutral point. However, analyzing and managing DELTA-connected loads can be complex, particularly when determining power distribution across phases. The invention addresses this by providing a mathematical method to convert DELTA-connected loads into equivalent WYE-connected loads, simplifying power flow analysis and control. The method calculates equivalent WYE-connected loads at each phase based on the active power of the DELTA-connected load between two phases and a power factor (cos ϕ D). The conversion uses two factors, β D+ and β D−, derived from the power factor's tangent. These factors adjust the active power values to distribute them across the phases in a WYE configuration. The active power of the DELTA-connected load between phases x and y (P Dxy) is split into two components: P Dxy-x and P Dxy-y, representing the equivalent loads at phases x and y. The conversion ensures accurate power distribution while maintaining system balance and simplifying further analysis. This approach is useful for power system modeling, load balancing, and fault detection in three-phase systems.
6. The method of claim 2 , wherein an available generation of the renewable generation is maximally used and a penalty cost is applied when there are unused but available renewable generation present, and the renewable generation is connected to a bus with WYE-connection or DELTA-connection.
This invention relates to optimizing the use of renewable energy generation in electrical power systems. The problem addressed is the underutilization of available renewable energy, which can lead to inefficiencies and wasted resources. The solution involves a method that maximizes the use of renewable generation by applying a penalty cost when unused but available renewable energy is present. This encourages full utilization of renewable resources. The renewable generation is connected to a power system bus configured in either a WYE (star) or DELTA (mesh) connection, which are common configurations in electrical distribution systems. The method ensures that renewable energy sources are fully utilized, reducing waste and improving system efficiency. The penalty cost mechanism acts as an incentive to prioritize renewable energy over other sources when available, thereby enhancing the integration of renewable energy into the grid. The system is designed to work with different connection configurations, making it adaptable to various power system setups. This approach helps balance energy supply and demand while minimizing reliance on non-renewable sources.
7. The method of claim 6 , wherein a DELTA-connected renewable generation between phases can be converted to equivalent WYE-connected renewable generations at each phase according to a power factor, cos ϕ G according to: P G xy - x = β G + P G xy , P G xy - y = β G - P G xy , β G + = 1 2 + 3 6 tan ϕ G , β G - = 1 2 - 3 6 tan ϕ G , wherein P G xy is the active power of the DELTA-connected renewable generation between phase x and phase y, P G xy-x and P G xy-y are active powers of equivalent renewable generations at phase x and phase y, β G + and β G − are conversion factors.
This invention relates to power conversion in electrical grids, specifically addressing the integration of renewable energy sources. The problem solved is the conversion of power from a DELTA-connected renewable generation configuration to an equivalent WYE-connected configuration, which is often required for compatibility with grid infrastructure. The method involves calculating active power contributions from each phase based on a power factor (cos ϕ G). The DELTA-connected generation between two phases (x and y) produces active power (P G xy), which is split into equivalent WYE-connected active powers (P G xy-x and P G xy-y) at each phase. The conversion uses two factors (β G + and β G −), derived from the power factor's tangent (tan ϕ G). These factors adjust the power distribution to maintain balance and compatibility with the grid. The method ensures accurate power allocation while accounting for phase-specific power factor variations, facilitating seamless integration of renewable energy into existing grid systems. This approach is particularly useful for optimizing power flow and stability in grids with distributed renewable generation.
9. The method of claim 8 , where the price the for unit up and down reserve usage, and the price for the unit up and down reserve usage variation are given in term of consumed energy at each pricing interval, and the up and down reserve usage and corresponding variation are determined as a summation of corresponding reserve usage or variation at each forecasting interval weighted by a ratio of a length of the forecasting interval over a length of the pricing interval.
This invention relates to energy reserve pricing and management in power systems, particularly for balancing supply and demand in real-time markets. The problem addressed is the need for accurate pricing and allocation of up and down reserve capacities, which are critical for maintaining grid stability. The solution involves determining the cost of reserve usage and its variations based on consumed energy over defined pricing intervals, while accounting for shorter forecasting intervals within those pricing intervals. The method calculates the total reserve usage and its variations by summing the reserve usage or variation at each forecasting interval, weighted by the ratio of the forecasting interval length to the pricing interval length. This approach ensures that reserve pricing reflects the actual energy consumption patterns over time, improving the accuracy of cost assessments. The pricing model considers both the base reserve usage and its dynamic variations, allowing for more precise financial settlements in energy markets. The method is particularly useful for grid operators and energy providers to optimize reserve capacity allocation and minimize costs while maintaining system reliability. By integrating forecasting intervals into the pricing calculation, the system better aligns reserve pricing with real-time operational conditions, enhancing market efficiency and fairness.
10. The method of claim 8 , where the price for unit up and down reserve usage, and the price for unit up and down reserve usage variation are given in term of used power capacity at each pricing interval, and the up and down reserve usage and corresponding variation are determined as a maximum of corresponding reserve usages or variations for all forecasting intervals of the pricing interval.
This invention relates to a method for pricing and managing reserve power capacity in energy systems, particularly for balancing supply and demand in electricity grids. The problem addressed is the need for an efficient and accurate pricing mechanism for reserve power usage and its variations, ensuring grid stability while optimizing costs. The method involves determining the price for both upward and downward reserve power usage, as well as the price for variations in that usage, based on the actual power capacity used during each pricing interval. The reserve usage and its variations are calculated as the maximum values of the corresponding reserve usages or variations across all forecasting intervals within a given pricing interval. This ensures that the pricing reflects the highest demand for reserves during the interval, promoting grid reliability. The method also includes forecasting reserve requirements over multiple intervals and selecting the maximum reserve usage or variation from these forecasts to set the pricing. This approach helps grid operators and energy providers accurately price reserve capacity, incentivizing efficient reserve deployment and reducing costs. The system ensures that reserve pricing aligns with real-time grid needs, improving overall grid stability and economic efficiency.
11. The method of claim 1 , where load control plans for all aggregated loads with flexibility are determined by satisfying following constraints, including: power balancing for each phase; power flow limitation for each branch at each phase; energy balancing for each transferable load at the phase or a phase pair; maximum unused active power for each renewable generation at the phase or the phase pair; maximum allowed reduced active power for each reducible load at the phase or the phase pair; and maximum allowed dropped active power for each removable load at a phase or a phase pair.
This invention relates to load control systems for managing electrical power distribution in multi-phase networks, particularly in environments with renewable energy sources and flexible loads. The problem addressed is the need to optimize power distribution while ensuring system stability, balancing power flows, and accommodating variable renewable generation and flexible demand. The method determines load control plans for aggregated loads with flexibility by enforcing multiple constraints. These include balancing power across each phase to prevent overloading, ensuring power flow within limits for each branch at every phase, and maintaining energy balance for transferable loads, which can shift between phases or phase pairs. Additionally, the method maximizes unused active power from renewable sources at specific phases or phase pairs, limits the reduction of active power for reducible loads, and restricts the shedding of active power for removable loads. The constraints collectively ensure efficient power utilization while maintaining grid stability and reliability. The approach is particularly useful in smart grids where renewable energy integration and demand-side management are critical for balancing supply and demand.
12. The method of claim 11 , power balancing for each phase is defined as for each bus of the PDS, an equivalent active power injected into the bus at the phase is be equal to the an equivalent active power extracted from the bus and the phase, the active power can be injected from the substation, a renewable generation or a branch connected to the bus, the active power can be exacted from the bus and the phase by a load or a branch connected to the bus; the generations and loads between phases are converted to equivalent generations and loads at corresponding phases.
Power balancing in electrical distribution systems (PDS) ensures stable operation by maintaining equilibrium between power injection and extraction at each phase of a bus. The method addresses imbalances caused by varying loads, renewable energy sources, and branch connections, which can disrupt system stability and efficiency. For each bus in the PDS, the method ensures that the total active power injected into a phase equals the total active power extracted from that phase. Power injection can originate from substations, renewable generation sources, or branches connected to the bus, while extraction occurs due to loads or branch connections. The method converts power contributions from multiple phases into equivalent values at their respective phases to simplify balancing calculations. This approach ensures that power flows are harmonized across phases, preventing overloading or underutilization of any single phase. The technique is particularly useful in modern grids with distributed energy resources, where power generation and consumption patterns are dynamic and unpredictable. By dynamically adjusting power distribution, the method enhances grid reliability and operational efficiency.
13. The method of claim 12 , power balancing for each phase is simplified as for the PDS, the equivalent active power injected into the PDS at the phase must be equal to the equivalent active power extracted from the PDS and the phase, the active power is injected from the substation, and the renewable generations; the active power is exacted from the PDS and the phase by the loads, and the generations and loads between phases are converted to equivalent generations and loads at corresponding phases.
This invention relates to power balancing in a power distribution system (PDS) with multiple phases, particularly in systems integrating renewable energy sources. The problem addressed is the complexity of balancing active power across phases to ensure stability and efficiency in the distribution network. The solution involves simplifying power balancing by ensuring that the equivalent active power injected into each phase of the PDS matches the equivalent active power extracted from that phase. Active power is injected into the phase from two sources: the substation and renewable energy generators. Conversely, active power is extracted from the phase by loads and any remaining generation not consumed locally. The method also accounts for power transfers between phases by converting inter-phase generations and loads into equivalent values at their respective phases. This approach standardizes power flow calculations, reducing computational complexity and improving real-time balancing in distributed energy systems. The technique is particularly useful in smart grids where renewable energy integration and dynamic load management are critical. By maintaining equilibrium between injected and extracted power per phase, the system avoids overloading, voltage instability, and inefficiencies, ensuring reliable and sustainable power distribution.
14. The method of claim 11 , power flow limitation for each branch at each phase is defined as active powers flowing on the branch through an upstream-bus and an downstream-bus of the branch on the phase are less than a capacity of the phase, active power flow flowing on the branch through the upstream-bus of the branch at the phase is determined as a summation of active power injections for all buses upstream to the upstream-bus of the branch, active power flow flowing on the branch through the downstream-bus of the branch at the phase is determined as a summation of active power injections for all buses downstream to the downstream-bus of the branch, and active power injection of a bus is determined a difference between a summation of active power injected from the substation and the available renewable generation connected to the bus and the phase, and a summation of active power extracted by all loads connected to the bus and the phase, and the generations and loads between phases are converted to equivalent generations and loads at corresponding phases.
This invention relates to power flow management in electrical distribution networks, specifically addressing the challenge of limiting power flow within the capacity constraints of each phase in a multi-phase system. The method ensures that active power flowing through any branch between an upstream bus and a downstream bus on a given phase does not exceed the phase's capacity. Active power flow through the upstream bus is calculated as the sum of active power injections from all buses upstream of the upstream bus, while active power flow through the downstream bus is the sum of active power injections from all buses downstream of the downstream bus. The active power injection at any bus is determined by the difference between the total active power supplied by the substation and any connected renewable generation, minus the active power consumed by loads connected to that bus and phase. The method also accounts for power generation and loads across different phases by converting them into equivalent values for the corresponding phases, ensuring balanced and efficient power distribution. This approach helps prevent overloading and ensures stable operation of the electrical network.
15. The method of claim 11 , energy balancing for each transferable load at the phase or a phase pair is defined as for the transferable load at the phase at a forecasting interval, active power of the load at the forecasting interval should be equal to a summation of active powers of equivalent loads transferred to other forecasting intervals, weighted by corresponding efficiencies for transferring load from the forecasting interval to other forecasting intervals.
This invention relates to energy balancing in electrical power systems, specifically for managing transferable loads across different phases or phase pairs to optimize energy distribution. The problem addressed is the need to efficiently balance active power demand across forecasting intervals while accounting for transfer losses and system constraints. The method involves determining the active power requirements for a transferable load at a specific phase during a forecasting interval. The active power of the load at that interval must equal the sum of active powers of equivalent loads transferred to other forecasting intervals, adjusted by the efficiency of transferring load between intervals. This ensures that energy is redistributed in a way that minimizes losses and maintains system stability. The approach considers the efficiency of load transfer, which varies depending on the direction and timing of the transfer, to optimize overall energy usage. By dynamically balancing loads across phases and intervals, the system can reduce peak demand, improve energy utilization, and enhance grid reliability. The method is particularly useful in smart grid applications where flexible load management is critical for maintaining balance between supply and demand.
16. The method of claim 1 , wherein an optimization problem for determining the load control plans is solved using the following steps: determining a candidate solution by omitting the constraints of power flow limitations; calculating the power flows after the candidate solution is obtained; and checking if overloaded branches are present, and if yes, resolving the optimization problem using the constraints of power flow limitation on the overloaded branches, and yielding a new solution; repeating the process until a solution is obtained without any overloaded branches.
This invention relates to power system optimization, specifically methods for determining load control plans to prevent overloaded branches in electrical networks. The problem addressed is the need to efficiently balance electrical loads while respecting power flow constraints to avoid system instability or damage. The method involves solving an optimization problem to generate load control plans. First, a candidate solution is generated by initially ignoring power flow limitations. Once this candidate solution is obtained, the power flows are calculated to identify any overloaded branches. If overloaded branches are detected, the optimization problem is resolved with additional constraints applied to those specific branches to prevent overload. This iterative process continues, refining the solution each time, until a final solution is reached where no branches are overloaded. The approach ensures that the load control plans are both efficient and compliant with power flow constraints, improving the reliability and stability of the electrical network.
17. The method of claim 1 , further comprising: adjusting the decoupled prices with respect to corresponding aggregated demand fluctuations, and further comprising: determining an aggregated demand profile at the substation by applied the load control plans to the PDS; increasing the up reserve price and decreasing the upper limit of the pre-determined normal range when the aggregated demand profile is above a pre-determined upper threshold; increasing the up reserve variation price when the up reserve usage variation among pricing intervals is above a pre-determined threshold; increasing the down reserve price and the lower limit of the pre-determined normal range when the aggregated demand profile is below a pre-determined lower threshold; and increasing the down reserve variation price when the down reserve usage variation among pricing intervals is above a pre-determined threshold.
This invention relates to dynamic pricing and demand management in power distribution systems (PDS). The technology addresses the challenge of balancing supply and demand in electrical grids by adjusting reserve prices and operational limits based on real-time demand fluctuations. The system monitors aggregated demand at substations and modifies pricing parameters to optimize grid stability and efficiency. The method involves determining an aggregated demand profile by applying load control plans to the PDS. If the demand exceeds a predetermined upper threshold, the system increases the up reserve price and raises the upper limit of the predefined normal operating range. Similarly, if demand variation among pricing intervals surpasses a set threshold, the up reserve variation price is adjusted upward. Conversely, when demand falls below a predetermined lower threshold, the down reserve price and the lower limit of the normal range are increased. If down reserve usage variation exceeds a threshold, the down reserve variation price is also raised. These adjustments ensure that reserve pricing dynamically responds to demand changes, preventing grid instability and improving resource allocation. The system enhances grid reliability by proactively managing reserve capacity and pricing based on real-time demand patterns.
18. A system for controlling power balancing at a substation of a power distribution system (PDS), comprising: a memory and input interface connected to a processor, the processor is configured to provide an amount of renewable generation to the substation of PDS using buses that inject renewable energy into the PDS using a transmission system at the substation for sharing renewable energy consumption between a predetermined number of load devices based upon predetermined aggregated load control plans to each load device to the substation of the PDS for a scheduling period; identifying from the scheduling period if situations in which an aggregated demand at the substation exceeds a predetermined limit, and upon determination of the aggregated demand exceeding the predetermined limit, then determine for a next scheduling period aggregate load control plans to each load device to the substation of the PDS in situations in which an aggregated demand at the substation exceeds a predetermined limit, wherein the aggregated demand is determined based on an energy demand of each load device and an amount of availability of renewable energy from the renewable generation; determine the aggregate load control plans for each load device to the substation of the PDS for the next scheduling period, based on specify decoupled price components for the substation of the PDS for all pricing intervals of the next scheduling period; acquire forecasts of load demands and renewable generations of the PDS for each forecasting intervals of the next scheduling period; determine load control plans for all aggregated loads with flexibility for each forecasting interval of the next scheduling period, wherein the load control plans are optimal; evaluate demand fluctuations at the substation based on the load control plans, and adjusting decoupled price components for the substation until the demand fluctuations at the substation are within a tolerance range; allocate, using an output interface connected to the processor, the aggregated load control plans to each load device of the substation of the PDS so the aggregated demand at the substation does not exceed the predetermined limit for the next scheduling period; and control an amount of power at the substation of the PDS for the next scheduling period by controlling each load device at the substation of the PDS based on adjusting an amount of power consumption and an amount of operation time of the load device during the next scheduling period according to the aggregated load control plans by lowering reducible loads, dropping removable loads and scheduling transferrable loads, according to the aggregate load control plans for each load device of the substation of the PDS.
The system controls power balancing at a substation in a power distribution system (PDS) by managing renewable energy integration and load demand. The system uses a processor connected to memory and input interfaces to distribute renewable energy from generation sources to load devices via substation buses. It schedules power consumption across multiple load devices based on aggregated load control plans for predefined scheduling periods. The system monitors aggregated demand at the substation and, if demand exceeds a predetermined limit, adjusts load control plans for the next scheduling period. Demand is calculated using each load device's energy demand and available renewable energy. The system determines optimal load control plans for flexible loads, considering decoupled price components for all pricing intervals in the next scheduling period. It also acquires forecasts of load demands and renewable generation for each forecasting interval. The system evaluates demand fluctuations and adjusts price components until fluctuations fall within an acceptable tolerance range. Finally, it allocates the adjusted load control plans to each load device to ensure substation demand stays within limits. Power control is achieved by modifying power consumption, operation time, and load types—reducing reducible loads, dropping removable loads, and scheduling transferrable loads—according to the optimized load control plans. This ensures stable power distribution while maximizing renewable energy utilization.
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July 14, 2020
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